文章利用近似逆矩阵构造了一类求解线性方程组的并行迭代算法。
In this paper, a parallel iterative algorithm for linear equations is given by approximating inverse of a matrix.
通过马尔可夫分析，构造了求解系统处于平稳状态概率的迭代算法，提出了计算订单的平均缺货水平的近似表达式。
Based on Markov analysis, this paper presents a recursive algorithm to compute probabilities under stable states and derives the approximate expression for order-based backorders.
文中涉及各种主要重建算，法包括准确重建，近似重建和迭代重建算法。
All the major types of reconstruction approaches are discussed, including exact algorithms, approximate algorithms, and iterative algorithms.
本文对于矩形区域上某一内点为奇点的奇异积分的近似计算给出了优化中心数值算法，它在迭代计算过程中避免了函数值的重复计算。
This paper presents an optimum numerical algorithm of center rule for the approximate evaluation of singular integrals over rectangular domains with a inner singularity.
利用这种等价性，构造了一些新的扰动近似点算法，并证明了由此算法所产生的迭代序列的收敛性。
Using this equivalence, we construct some new perturbed proximal point algorithms and prove the convergence of iterative sequences generated by the algorithms.
基于一种新的线性化近似模型，提出一类双层最优迭代算法。
According to the model, a new dual-staged optimal iterative learning control scheme is proposed.
算法使用了局部图的思想，使每次迭代更新尽量少的节点来减少代价。实验证明算法具有良好的效率、近似度和可伸缩性。
Based on the concept of Local map, the algorithm tries to update as few nodes as possible to reduce cost.
算法使用了局部图的思想，使每次迭代更新尽量少的节点来减少代价。实验证明算法具有良好的效率、近似度和可伸缩性。
Based on the concept of Local map, the algorithm tries to update as few nodes as possible to reduce cost.
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